The Liverpool University Drug Interactions group has over twenty years' experience in developing prescribing support resources in infectious diseases, demonstrated by our world-renowned HIV and Hepatitis drug interaction websites (www.hiv-druginteractions.org and www.hep-druginteractions.org) and associated Apps. In 2019, these websites had over 50,000 unique monthly visitors searching for >4.5 million interactions. Our websites are recommended in over 30 international treatment guidelines and many national guidelines. In response to the COVID-19 pandemic and to address the pressing need for prescribing support for studies and clinical situations where experimental COVID-19 therapies are being used, we have developed a static drug interactions website (www.covid19-druginteractions.org) providing information on the likelihood of interactions between the experimental agents and commonly prescribed co-medications. We now have to move to develop a fully interactive and searchable website resource with an associated App. The website will be constantly updated and populated with the latest information on experimental therapies with guidance given to clinicians for managing complex patients.

Immune-mediated inflammatory diseases (IMIDs) are common medical conditions that cause substantial pain, distress, loss of function and early death. They are clinically diverse e.g. by variously targeting the skin, joints, or kidneys, but share some common genetic features, environmental triggers and inflammatory pathologic mechanisms. The IMIDs include rheumatoid arthritis (RA), psoriasis, systemic lupus erythematosus (SLE), Sjogren's syndrome, autoimmune hepatitis and primary biliary cirrhosis. Since the 1990s, biologic drugs and improved treatment strategies have revolutionised the treatment of a significant proportion of people with some IMIDs. However some IMIDs have not really progressed and even in those in which advances are notable, many patients do not yet respond to treatment or lose their responses over time - this in life long incurable diseases. Therefore, there remains great unmet clinical need in the IMID field. One exciting approach to improving outcomes is to apply the principles of precision medicine whereby patients will receive the 'right drug at the right time at the right dose' with minimal chance of having significant toxicity. Bringing precision medicine to IMIDs will require large datasets that integrate clinical information together with complex molecular datasets that can now be generated from the blood and damaged tissues that occur in IMIDs. In theory, by putting this information together we can create a 'molecular map' of a patient that allows very precise treatment decisions to be made that will bring better outcomes at reduced risk. Thus far however most IMID collections of such data have been specified for only one disease leading to a rather narrow approach to the broader inflammation medicine field. This proposal will revolutionise this scenario by bringing together many UK biobank and clinical cohort datasets into one single searchable and analysable entity, lead and coordinated by a consortium called IMIDBio-UK. IMIDBio-UK will generate a virtual information superhighway that will allow unprecedented access to information about IMIDs across the UK. The vision of the IMID-Bio-UK consortium is to harness the power of a rich reserve of biosamples, deeply phenotyped clinical cohorts, and high quality multi-omic data formed from a group of highly successful national stratified medicine programmes. These resources will be made available to researchers to study IMID biology and predict drug response, using molecular markers (biomarkers) to define common and unique mechanisms (endotypes) of disease progression and drug action. This will enable wider, safer use of biologics and new medicines across the IMID spectrum. By bringing together IMID samples and comparing data and clinical practice, we will optimise clinical pathways for common IMIDs, and provide much needed insight into biologic use in rarer or poorly characterised IMIDs, ultimately delivering patient benefit and health care savings.

Childhood arthritis, classified under the umbrella term juvenile idiopathic arthritis, JIA, and its associated eye inflammation, JIA-uveitis, can be devastating for both child and family, and impose significant long-term economic burden on society. Despite improvements in the management of JIA, and increasing availability of new medicines, many children still undergo prolonged treatment with multiple drugs that may not work, leaving them exposed to uncontrolled inflammation, side effects, and the damaging effects of disease, which include disability, vision loss, lower quality of life and reduced chances of employment. Early control of childhood arthritis and JIA-uveitis translates to better longterm outcomes and economic benefit. However, current JIA classification does not inform choice of drug for most children, and there are no verified clinical or biological tools with which to predict disease course, select treatment or predict response. Effective strategies allowing doctors to choose the right medicine, at the right time for each child ('stratified medicine'), would increase early remission rates, reduce suffering, improve long-term outcomes and avoid years of treatment with ineffective drugs. To start to address these unmet needs, we established a partnership between 4 large UK JIA cohort studies, the Childhood Arthritis Response to Treatment (CHART) Consortium, representing 5000 children with JIA, with clinical information, biological samples, and new data. Building on our success, and strengthened by important new cohorts and investigators, we now propose an ambitious consortium, CLUSTER, bringing together internationally recognised leaders in childhood arthritis and JIA-uveitis, with new collaborators and industry partners to deliver stratified medicine for JIA. CLUSTER will include multidisciplinary expertise in clinical, molecular, genetic, immunological, and statistical sciences, with UK leaders in paediatric rheumatology and ophthalmology, and those designing and delivering clinical trials in JIA and its associated uveitis. The overall goal of CLUSTER is to define 'endotypes' (subgroups based on underlying disease mechanism) of childhood arthritis and JIA-uveitis, which more accurately reflect likely treatment response and disease course, linked to biomarkers that are feasible to measure in children, to allow targeted treatment decisions. We will adopt a P4 (predict, prevent, personalise, participatory) approach; our key scientific aims are to: 1. Identify 'biomarkers' (clinical, genetic, protein, gene expression or immune factor) that help predict treatment response in JIA, to allow a more targeted approach to medicine choices and prevent poor long-term outcomes; 2. Identify predictors (clinical, genetic, auto-antibody) of getting uveitis for children with JIA, to improve screening protocols and prevent vision loss; 3. Using specimens from both blood and inflamed joints, undertake state of the art analysis of cells, proteins and gene expression in JIA to define mechanisms of response to treatment and different disease types, and identify new treatments; 4. Integrate and explore all CLUSTER data together to define endotypes in JIA, that predict disease type or treatment response, with associated markers that can be measured, to enable personalised treatment and facilitate patient/parent participation in treatment choices; 5. Establish collaborative agreements with Industry and international partners to ensure that high-quality bio-sample collection and stratification design are used in future trials in childhood arthritis and uveitis. Our programme of work will speed up the introduction of 'stratified' medicine for children with JIA. Earlier control of inflammation and reduced exposure to side effects will allow children to return to their education and full sporting and family life activities, prevent life long disability and blindness, and reduce costs to the health service and society as a whole.